Systems and methods of determining a location of a mobile container

ABSTRACT

A system for locating a mobile container within a facility comprises an optical sensor system with an optical sensor fixed to a frame of the container. The optical sensor is pointed away from the container in a direction facing a region of the facility (e.g., ceiling or floor) where one or more distinctive physical features are expected to be found. Each distinctive physical feature of the facility is associated with a location in the facility. The optical sensor is adapted to capture an image of that region of the facility. A computing system includes a processor configured to receive the image from the optical sensor, to determine that a physical feature found in the image matches one of the distinctive physical features of the facility, and to identify the container as being at the location in the facility associated with the matching distinctive physical feature.

RELATED APPLICATION

This application claims the benefit of and priority to U.S. ProvisionalApplication No. 62/590,133 titled “Container Location DeterminationMethodology,” filed on Nov. 22, 2017, the entirety of which provisionalapplication is incorporated by reference herein for all purposes.

FIELD OF THE INVENTION

The invention relates generally to mobile item-collection containers.More particularly, the invention relates to such mobile containershaving an integrated machine-vision system for determining the locationof the containers within an indoor environment.

BACKGROUND

Understanding how shoppers navigate stores and make purchasing decisionscan provide a wealth of information to various businesses. Suchinformation includes which aisles the shoppers visit, and the amount oftime spent in those aisles. Current state-of-the-art technology, such asGPS (Global Positioning System) can track the movement of shoppersthrough a store and generate tracking data but tend to be imprecise whenpinpointing location. Other machine-vision technologies rely onoptically read barcodes or special tags to identify locations within afacility, but such methods require modification to the facility toinstall these coded items.

SUMMARY

All examples and features mentioned below can be combined in anytechnically feasible way.

In one aspect, the invention relates to a system for locating a mobilecontainer within a facility comprising an optical sensor system havingat least one optical sensor fixed to a frame of the container. Eachoptical sensor is pointed away from the container in a direction facinga region of the facility where one or more distinctive physical featuresare expected to be found. Each distinctive physical feature of thefacility is associated with a location in the facility. The at least oneoptical sensor is adapted to capture an image of that region of thefacility. The system also comprises a computing system in communicationwith the at least one optical sensor fixed to the frame of thecontainer. The computing system includes a processor configured toreceive the image from the at least one optical sensor, to determinethat a physical feature found in the image matches one of thedistinctive physical features of the facility, and to identify thecontainer as being at the location in the facility associated with thematching distinctive physical feature.

In one embodiment, the optical sensor system includes an infraredprojector for projecting a distinct pattern used by the computing systemto calculate depth. The infrared projector may be a camera separate fromthe at least one optical sensor or part of one optical sensor of the atleast one optical sensor.

The computing system may be disposed remotely from the container and isconfigured to communicate wirelessly with the one or more opticalsensors to the receive the image.

In some embodiments, one of the at least one optical sensor facesupwards towards a ceiling of the facility, downwards towards a floor ofthe facility, horizontally, parallel to a floor of the facility, or anycombination thereof.

One or more distinctive physical features may include ductwork at aceiling of the facility. The system may further comprise a databasestoring images of the one or more distinctive physical features of thefacility and associating each stored image with a location in thefacility. The processor of the computing system may be configured tomatch the physical feature in the captured image with a distinctivephysical feature in a given image stored in the database and to identifya location of the container as the location associated with the givenimage in response to the match.

In one embodiment, the system may further comprise a radio-frequencyreceiver disposed on the container. The RF receiver receives a radiosignal at a given radio frequency and the processor of the computingsystem is configured to determine a location of the container based on arelative strength of the given frequency of the received radio signal.

In another aspect, the invention relates to a method for locating amobile container within a facility comprising the steps of associating adistinctive physical feature of the facility with a location in thefacility; acquiring, by an optical sensor fixed to a frame of the mobilecontainer, an image of a region of the facility; detecting a physicalfeature in the acquired image; matching the physical feature detected inthe acquired image with the distinctive physical feature of thefacility; and identifying the container as being at the location in thefacility associated with the distinctive physical feature in response tomatching the physical feature detected in the acquired image with thedistinctive physical feature of the facility.

The region of the facility in the acquired image may be of a ceiling ofthe facility, of a floor of the facility, of a region of the facilityhorizontally parallel to a floor of the facility. The acquired image maybe of a ceiling of the facility and a second acquired image may be of afloor of the facility.

The method may further comprise storing images of distinctive physicalfeatures in the region of the facility in a database and associatingeach stored image with a location in the facility. The method mayfurther comprise matching the physical feature detected in the acquiredimage with a distinctive physical feature in a given image stored in thedatabase and identifying a location of the container as the locationassociated with the given image in response to the match.

The method may further comprise receiving by a receiver, disposed on aframe of the mobile container, a radio signal having a given radiofrequency and determining a location of the mobile container based on arelative strength of the given frequency of the received radio signal.

In another aspect, the invention is related to a system for locating acart within a facility comprising an inertial measurement unit (IMU)fixed to the cart. The IMU is adapted to sense direction and speed asthe cart moves and to report information related to the sensed directionand speed. The system further comprises a computing system incommunication with the IMU. The computing system includes a processorconfigured to receive the information related to the direction and speedsensed and transmitted by the IMU and to determine a present location ofthe cart within the facility based on the information received from theIMU.

The system may further comprise a database that stores a map of thefacility. The processor of the computing system is configured to overlayon the map an initialized location of the IMU and movement of the IMUbased on the sensed direction and speed to determine the presentlocation of the cart within the facility. The database may store loci oftransmitted signals, which over time reveal individual and aggregatetraffic patterns.

In another aspect, the invention relates to a system for locating amobile container within a facility comprising an optical sensor fixed toa frame of the container. The optical sensor is pointed away from thecontainer in a direction facing a region of the facility where one ormore distinctive physical features of the facility are expected to befound. The optical sensor is adapted to capture an image of that regionof the facility. A computing system, in communication with the opticalsensor, includes a processor configured to receive the captured imagefrom the optical sensor, to identify a distinctive physical feature ofthe facility in the captured image received from the optical sensor, andto determine a location of the container based on the identifieddistinctive physical feature. The system may further comprise a databasethat stores images of the one or more distinctive physical features ofthe facility and associates each stored image with a location in thefacility. The processor of the computing system is configured to matchthe distinctive physical feature found in the captured image with adistinctive physical feature in a given image stored in the database andto identify a location of the container as the location associated withthe given image.

BRIEF DESCRIPTION OF THE DRAWINGS

Various aspects of at least one embodiment are discussed below withreference to the accompanying figures, which are not intended to bedrawn to scale. The figures are included to provide illustration and afurther understanding of the various aspects and embodiments, and areincorporated in and constitute a part of this specification, but are notintended as a definition of the limits of the invention. In the figures,each identical or nearly identical component that is illustrated invarious figures is represented by a like numeral. For purposes ofclarity, not every component may be labeled in every figure. In thefigures:

FIG. 1 is a side view of an embodiment of a cart with an integratedmachine-vision system; and

FIG. 2 is a block diagram of an embodiment of the machine-vision system;and

FIG. 3 is a flow diagram of an embodiment of a process for determiningthe location of a cart, having an integrated machine-vision system,within an indoor environment.

FIG. 4 is a diagram of an embodiment of system for determining thelocation of a mobile container using radio-frequency technology.

DETAILED DESCRIPTION

Container-locating systems described herein allow the locating andtracking of a shopping basket, cart, or other container, automatically,and with high confidence, throughout a store, warehouse, or other indoorenvironment. These locating systems are especially useful in commercialinventory and retail shopping environments, providing convenient andunobtrusive ways to track goods, workers, and shoppers as they moveabout a facility.

For shoppers in a retail environment, as an example, such locatingsystems can improve the shopper's experience, for instance, by assistingthe shopper in locating items on a shopping list and identifying anefficient route to picking the items on the shopping list. Additionally,such locating systems can offer promotions or guide customers to locatedifficult-to-find items, bathrooms, or exits. As another example, in awarehouse environment, such locating systems can help managers monitoremployee activity; and the locating systems can help employees engagedin a picking operation identify the location of an item and show anefficient pathway to pick items as they traverse through the warehouseor inventory room.

Further, such locating systems can collect and present a wealth ofinformation to the management of a facility, for example, the trafficpatterns of containers and, by implication, the people associated witheach container. Management can then use this information for a varietyof purposes, for example, to improve traffic flow at peak congestiontimes or to rearrange the goods in the facility for increasedvisibility.

FIG. 1 shows a side view of an embodiment of a shopping cart 100 havinga frame 102 on wheels 104, a basket 106 coupled to the frame 102, and amachine-vision system 200 (FIG. 2). The construction of the shoppingcart may be made of metal, plastic, or a combination thereof and/or ofother materials, for example wood. The principles described hereinextend to other examples of carts, which include, but are not limitedto, carriages, carriers, trolleys, buggies, picker cart, grocery carts,and supermarket carts.

The frame 102 of this embodiment of shopping cart 100 has horizontalbase rails 110 (one visible) and uprights 112 (one visible). The baserails 110 are located just above the wheels 104. Extending rearward froma back cross rail (not shown) is a handle 114 by which a person cangrasp and move the shopping cart 100.

The wheels 104 of the shopping cart can be caster wheels, of the swivelor rigid variety. For example, the front two wheels can be swivel, whilethe rear two wheels are rigid. Alternatively, all four wheels can berigid, or all four wheels can be swivel. The shopping cart 100 can havefour wheels, one wheel at each corner of the cart, or, in otherembodiments, three wheels, one in front center and two in the back. Thebasket 106 is, in this embodiment, a lattice, having a top edge 116,opposing side walls 118, a front wall 120, a back wall 122, and a bottomtray 124. The basket may also be referred to as a bin, container, orholder. The top edge 116 of the basket may be considered part of theframe 102 of the cart.

Components of the machine-vision system 200 include a computing system108 in communication with at least one optical sensor 126 (i.e., acamera). Each optical sensor 126 can be an BW or RGB image camera orvideo camera, and can include depth sensing capability, embodied withina single camera, such as, for example, Microsoft's Kinect™, or embodiedin separate devices, for instance, an optical sensor system comprising acamera and a separate infrared projector.

In the embodiment shown, the cart 100 has two optical sensors 126-1,126-2 (generally, 126), both fixed within the frame 102 of the cart.Optical sensor 126-1 is disposed at a top end of the upright 112 and hasa field of view 127 that points upwards towards the ceiling of thefacility. Optical sensor 126-2 is disposed at one end of the horizontalbase rail 110 and has a field of view 128 that points downwards towardsthe floor of the facility. The locations of the optical sensors 126 areillustrative examples; the locations of optical sensors 126 can beanywhere on the frame or basket (e.g., top edge 116) capable ofsupporting the attachment of a camera, provided such optical sensors 126are positioned to take images of the ceiling and/or floor of thefacility.

Embodiments of the cart 100 can have one or more ceiling-facing cameras(without any floor-facing cameras), one or more floor-facing cameras(without any ceiling-facing cameras), or a combination of ceiling-facingand floor-facing cameras. Embodiments of the cart 100 can also haveoptical sensors aimed horizontally, parallel to the surface of thefloor, that captures image or video data in front of, behind, and/or tothe sides of the cart. Such optical sensors can capture images ofshelves or other physical features at “eye level” to that opticalsensor.

The computing system 108 is also embodied within the frame 102 (FIG. 1is a cutaway view that passes through the upright 112 and the base rail110 to show the sensors 126 and computing system 108 housed within theframe). Wires 130 connect the optical sensors 126 to the computingsystem 108 and transmit image or video data captured by the opticalsensors to the computing system.

The location of the computing system 108 on the cart, with the wiredconnections to the optical sensors 126, is an illustrative example; inanother embodiment, the computing system can reside remotely, and theoptical sensors 126 can communicate with the computing system wirelessly(e.g., BLUETOOTH®, Wi-Fi, radio signals). In one embodiment, thecomputing system 108 can be in communication with a display screen (notshown) mounted to the frame 102, basket 106, or handle 114 of the cart100 wherever the display screen can facilitate user interaction and easeof use. The computing system 108 can present on the display screen auser interface screen that permits interaction with the employee orshopper.

In an embodiment of the cart, the computing system 108 on the cartincludes an inertial measurement unit (IMU) device (not shown). The IMUdevice senses direction and acceleration of the cart and transmitsinformation (data) related to the sensed direction and acceleration. Anexample embodiment of the IMU device is the MPU-6050 manufactured byInvenSense of San Jose, Calif. From the information produced by the IMUdevice, the computing system can calculate the current location of thechip. By recording the accumulation of loci, the computing device cancalculate the path of the cart taken through the facility. The computingsystem can trigger the IMU device to start (or restart) at a specificpoint (e.g., at the store entrance) to establish the reference locationto which the calculations are applied. Other triggers to initialize theIMU device include, but are not limited to, a manual restart anddetecting that the cart is at a specific location within the facility(e.g., the store entrance). The calculated movement of the cart can beoverlaid with a map of the facility, to provide not only informationabout the path of movement of the cart through the facility, but alsoabout how long the cart sits motionless at times in the store (e.g., howlong a shopper paused before the shampoo display). Embodiments of thecart with the IMU chip can also include a machine-vision system, such asthat described herein, by which the computing system can establish thereference (and/or subsequent) location of the cart. The results derivedfrom the IMU can be used to confirm those of the machine-vision system,or the results of the machine-vision system to confirm those of the IMU.

In brief overview, during operation of the container-locating system100, the computing system 108 receives an image from one or more of theoptical sensors 126, identifies physical feature(s) in the image,determines that a physical feature found in the image corresponds to adistinctive physical feature known to be at a given location in thefacility (e.g., by comparing the features identified in the image withan existing database of images of features in on the floor or on theceiling in the facility), and, because of that determination, identifiesthe cart as being at that given location. The operation of thecontainer-locating system 100 involves feature detection in thecart-captured images and feature matching with images in a library(i.e., matching appearances), not reading and decodingposition-identifying patterns or codes placed on the ceiling or thefloor.

In one embodiment, described in detail in connection with FIG. 4, thecart 100 includes a radio-frequency (RF) receiver (not shown). Aplurality of RF tags or beacons are placed around a facility, forexample, on store shelves. Each RF tag or beacon transmits an RF signalat a frequency unique to that RF tag or beacon. The RF receiver on thecart receives the RF signal. Software executing on the computing system108 (local to the cart) searches for a match to the unique frequency ofthe received radio signal in a database that associates unique signalfrequencies to RF tags or beacons and such RF tags or beacons tolocations in the facility. By a match, the system has identified thelocation of the RF transmitter and, in combination with an analysis oftransmitted signal strength, hence, the location of the cart. Thislocation of the cart, determined by this received RF signal, can be usedto confirm the location determination made by the computing system basedon an image captured by an optical sensor on the cart. If there arenumerous RF tags or beacons in a location, the software executing on thecomputing system 108 calculates the relative strength of each signal andfrom that strength data, determines the location of the receiver, and,therefore, the location of the cart with the receiver.

FIG. 2 shows an embodiment of the machine-vision system 200 includingthe computing system 108, one or more optical sensors 126, optionallyone or more infrared pattern depth sensors 202, an image database 204,and an optional display screen 206. Instead of depth sensors, depthsensing (i.e., distance calculations) can be obtained by comparing thedifferences between images obtained by a plurality of optical sensors.For instance, knowing the position of a camera and a light source, thecomputing system can determine by shadow size, direction, and length,how far away a distinctive feature is. Comparing images from twoseparate cameras (or imaging points) can provide this distanceinformation, too.

The computing system 108 includes a processor 208 in communication withmemory 210, each optical sensor 126, each optional depth sensor 202, theimage database 204, and the optional display screen 206. Stored in thememory 210 is software, including a machine-vision module 212, which,when executed by the processor 208, performs the image-processing,feature matching, and cart locating operations described in more detailin connection with FIG. 3. Software also stored in the memory 210 is auser interface module 214, which, when executed by the processor 208,produces a user interface on the display screen 206. This user interfacemay function as an entertainment portal, an internet connection, anemergency-information transmitter, or other screen-based computerfunctions.

The software stored in the memory 210 can also include an applicationprogram 216 that communicates with a corresponding application programexecuting on a mobile device (e.g., smartphone) of the shopper, forexample, by electronic mail, near-field communications (NFC) orBLUETOOTH®, to acquire, for example, the user's shopping list, or, inwarehouse applications, a picker's list. The computing system candisplay this list on the user interface produced on the display screen206. Alternatively, if there's a display screen 206 with an interactiveuser interface, the shopper can enter the shopping list of desired itemsmanually (e.g., at the start of their shopping trip). In anotherexample, which involves the Internet Things (IoT), the shopper cancreate the shopping list at home (or other site other than the shoppingfacility) and email the list or otherwise electronically transmit thelist to the facility or an intermediate service, such as a smartphoneapp.

The image database 204 contains a library of images taken of regions ofthe ceiling and/or of the floor of the facility. Each stored imageincludes one or more clearly visible, distinctive physical features ofthe photographed region. A physical feature is considered distinctive ifit's appearance (and immediate surroundings) can be unambiguously tiedto a specific location within the facility and to no other location.Such distinctive features may be three-dimensional or two-dimensional inshape; some such features are integral or built-in physical features ofthe structure or construction of the facility; other distinctivefeatures are intentional and unintentional modifications to the ceilingand/or floor. Examples of distinctive features of a ceiling include, butare not limited to, heating, venting, and air conditioning ductwork,pipework, plumbing, wiring, fuse boxes, lights, skylights, sprinklersystems, and support structures, such as trusses, a broken light, amissing ceiling tile. Examples of distinctive physical features of afloor include, but are not limited to, floor coverings and patternscontained therein, transitions in floor coverings, door jambs, and othersurface characterizations, such as bathroom tile, indicating a bathroomlocation, or dents, scratches, visible wear on a carpet, rubber trackson a concrete floor, and other unique marks that uniquely signify aphysical location within a facility. Each distinctive feature in astored image may be catalogued (i.e., identified and named) within thedatabase 204 and associated with that image to facilitate featurematching.

Each image stored in the image database 204 is also cross-referenced orassociated with the location in the facility of the photographed region.For example, an image stored in the image library of a broken lightknown to be at the intersection of row A with aisle 3 is associated inthe image database 204 with that location. An image captured by anoptical sensor of a broken light that matches the stored image of thebroken light thus identifies the location of the cart as theintersection of row A with aisle 3, namely, the location associated withthat stored image.

One embodiment of a cart 100 has optical sensors aimed horizontally,parallel to the surface of the floor. To accommodate such carts, theimage database 204 can further include images of distinctive physicalfeatures expected to be in the field of view of these cameras, forexample, shelves, wall sockets, displays, and checkout counters, formatching with captured images. Because personnel and shoppers often addand remove merchandise from shelves, and personnel can rearrangeshelves, images captured by these horizontally aimed optical sensors maynot be reliably matched with images in the image database. Instead ofrelying wholly these optical sensors for locating the cart, thelocating-system can supplement the results obtained from those opticalsensors pointing to the ceiling and/or the floor. A cart locationderived from a horizontally aimed optical sensor can be used to doublecheck a cart location derived from a vertically aimed optical sensor(i.e., one facing up or down).

Embodiments of the cart 100 that have a ceiling-facing camera and afloor-facing camera may conceivably have one of the cameras capture animage of a distinctive feature while the other camera does not. Whenboth types of cameras capture an image of a distinctive feature (one onthe floor, the other at the ceiling), the computing system can use thelocation determined from the one camera to confirm the locationdetermination of the other.

To populate the image database 204 with the images of pertinent regionsof the facility, feature identification, and associated locationinformation, the processor 208 executes a teaching module 218. Throughthis teaching module 218, the processor 208 “trains” or “teaches” thedatabase 204 with images of distinctive physical features on the ceilingand/or floor (and/or, optionally, e.g., shelves) taken by personnel. Theteaching module 218 can stitch the images together to produce a map ofeither or both the ceiling and the floor, with the identified (known)locations of each distinctive feature in the map(s). The map ofstitched-together images serves as an illustrative example by which thedatabase associates stored images with facility locations. Accordingly,a map of the ceiling of the store can show, for example, every sectionof duct work and every lighting fixture. By comparing an acquired imageof a broken light against the stored map of the ceiling, the systemfinds the part of the map with the matching image and identifies thelocation of the cart based on the location of the matching image in themap.

Although the processor 208 is described herein as executing all thesoftware stored in memory 210, it is to be understood that differentprocessors of different computing systems can execute different ones ofthe software modules or application programs.

FIG. 3 shows an embodiment of an automated process 300 for determiningthe real-time location of the cart within a facility. At step 302, anoptical sensor captures an image of the ceiling (or floor) at a locationwithin the facility and transmits the image to the computing system. Theimage captured by the optical sensor has the resolution necessary toallow the effective extraction of details for purposes of recognizing adistinctive physical feature, for example, the size and type of ductwork. The computing system executes the machine-vision module 212 toperform image processing techniques that optionally preprocess theimage, analyze the image, and attempt to detect distinctive features init. For example, from an image or series of images acquired by a cameraon the cart, the processor can derive the distance of a physical featurefrom the camera. The processor can also determine the perspective andcurvature from depth information acquired, provided the camera thatacquired the image has depth sensing capabilities. The processor can usethe distance and perspective to scale and shear the captured image forpurposes of matching the image resolution of those images stored in theimage library.

The image processing of the captured (and, optionally, preprocessed)image finds (step 304) key points in the image. Detected key points forpurposes of image matching can include size and color distribution inaddition to salient visual descriptors. For example, the detected keypoints can be the four corners of an air vent in the ceiling. Standardimage matching techniques, such as SURF (Speeded Up Robust Features) andSIFT (Scale Invariant Feature Transform), can be used to find such keypoints. The computing system uses these detected key points to search(step 306) the image database 204 for an image with matching distinctivefeatures. In response to finding a matching image, the computing systemacquires, from the image database 204, the location in the facilityassociated with the matched image. This location corresponds to thelocation where the optical sensor captured the image of, for example,the air vent in the ceiling. The computing system records (step 310)this location as the present (i.e., last known) location of the cart.

The computing system can display the determined present location of thecart in the user interface (along with any other information thefacility may choose) on the display screen 206 (FIG. 2). Through thisuser interface screen, the computing system can direct employees orshoppers from the present location of the cart toward the locations ofitems for which they are searching. The computing system may advertisealternative items or promotions to the user through the user interfacescreen.

Other actions that can be performed after the distinctive features(i.e., key points) in a captured image are matched to the distinctivefeatures of an image stored in the image library 204 include, but arenot limited to, determining a path through the facility from successivematched location points and associating time stamps with each locationpoint along on path to track the history of the movement of thecontainer through the facility, comparing the present location of thecontainer with previously recorded paths taken through the facility andanticipating a future path.

FIG. 4 shows an example of determining the location of a cart 403 usingradio-frequency technology. The description of this example isoversimplified to demonstrate more clearly the principles of this mannerof location determination. Three radio-frequency beacons 405 are placedwithin a facility. In this example, the cart 403 has a computing device(not shown) in which a radio receiver is embedded. Because radio signalsdecrease in strength over distance, the distance from eachRF-transmitting beacon can be determined by signal strength. Comparingthe relative strength of the beacons allows the computing device todetermine cart location. In this example, the cart 403 is located nearthe entrance 401 of the store and receives signals from the beacons405-1, 405-2, and 405-3. The strength of the beacon 405-1 at the end ofthe first aisle is the strongest signal. The signals from the beacon405-2 at the far end of the fourth aisle and the signal from the beacon405-3 at the front end of the last aisle are similar in strength becausethey are approximately equidistant from the cart. Thus, the computingdevice can determine the cart is in the front of the store, closer tothe entrance 401 than the exit 402.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method, and computer programproduct. Thus, some aspects of the present invention may be embodiedentirely in hardware, entirely in software (including, but not limitedto, firmware, program code, resident software, microcode), or in acombination of hardware and software.

In addition, aspects of the present invention may be in the form of acomputer program product embodied in one or more computer readable mediahaving computer readable program code stored thereon. Any combination ofone or more computer readable medium(s) may be utilized. The computerreadable medium may be a computer readable signal medium or a computerreadable storage medium. The computer readable medium may be anon-transitory computer readable storage medium, examples of whichinclude, but are not limited to, an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus, ordevice, or any suitable combination thereof.

As used herein, a computer readable storage medium may be any tangiblemedium that can contain or store a program for use by or in connectionwith an instruction execution system, apparatus, device, computer,computing system, computer system, or any programmable machine or devicethat inputs, processes, and outputs instructions, commands, or data. Anon-exhaustive list of specific examples of a computer readable storagemedium include an electrical connection having one or more wires, aportable computer diskette, a floppy disk, a hard disk, a random accessmemory (RAM), a read-only memory (ROM), a USB flash drive, annon-volatile RAM (NVRAM or NOVRAM), an erasable programmable read-onlymemory (EPROM or Flash memory), a flash memory card, an electricallyerasable programmable read-only memory (EEPROM), an optical fiber, aportable compact disc read-only memory (CD-ROM), a DVD-ROM, an opticalstorage device, a magnetic storage device, or any suitable combinationthereof.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device. As used herein, acomputer readable storage medium is not a computer readable propagatingsignal medium or a propagated signal.

Program code may be embodied as computer-readable instructions stored onor in a computer readable storage medium as, for example, source code,object code, interpretive code, executable code, or combinationsthereof. Any standard or proprietary, programming or interpretivelanguage can be used to produce the computer-executable instructions.Examples of such languages include Python, C, C++, Pascal, JAVA, BASIC,Smalltalk, Visual Basic, and Visual C++.

Transmission of program code embodied on a computer readable medium canoccur using any appropriate medium including, but not limited to,wireless, wired, optical fiber cable, radio frequency (RF), or anysuitable combination thereof.

The program code may execute entirely on a user's device, such as themobile device 140, partly on the user's device, as a stand-alonesoftware package, partly on the user's device and partly on a remotecomputer or entirely on a remote computer or server. Any such remotecomputer may be connected to the user's device through any type ofnetwork, including a local area network (LAN) or a wide area network(WAN), or the connection may be made to an external computer (forexample, through the Internet, using an Internet Service Provider).

Additionally, the methods of this invention can be implemented on aspecial purpose computer, a programmed microprocessor or microcontrollerand peripheral integrated circuit element(s), an ASIC or otherintegrated circuit, a digital signal processor, a hard-wired electronicor logic circuit such as discrete element circuit, a programmable logicdevice such as PLD, PLA, FPGA, PAL, or the like. In general, any devicecapable of implementing a state machine that is in turn capable ofimplementing the proposed methods herein can be used to implement theprinciples of this invention. In these instances, the systems andmethods of this invention may be implemented as program embedded onpersonal computer such as JAVA® or CGI script, as a resource residing ona server or graphics workstation, as a plug-in, or the like. The systemmay also be implemented by physically incorporating the system andmethod into a software and/or hardware system.

Furthermore, the disclosed methods may be readily implemented insoftware using object or object-oriented software developmentenvironments that provide portable source code that can be used on avariety of computer or workstation platforms. Alternatively, thedisclosed system may be implemented partially or fully in hardware usingstandard logic circuits or a VLSI design. Whether software or hardwareis used to implement the systems in accordance with this invention isdependent on the speed and/or efficiency requirements of the system, theparticular function, and the particular software or hardware systems ormicroprocessor or microcomputer systems being utilized. The methodsillustrated herein however can be readily implemented in hardware and/orsoftware using any known or later developed systems or structures,devices and/or software by those of ordinary skill in the applicable artfrom the functional description provided herein and with a general basicknowledge of the computer and image processing arts.

Having described above several aspects of at least one embodiment, it isto be appreciated various alterations, modifications, and improvementswill readily occur to those skilled in the art. Such alterations,modifications, and improvements are intended to be part of thisdisclosure and are intended to be within the scope of the invention.Embodiments of the methods and apparatuses discussed herein are notlimited in application to the details of construction and thearrangement of components set forth in the foregoing description orillustrated in the accompanying drawings. The methods and apparatusesare capable of implementation in other embodiments and of beingpracticed or of being carried out in various ways. Examples of specificimplementations are provided herein for illustrative purposes only andare not intended to be limiting. References to “one embodiment” or “anembodiment” or “another embodiment” means that a feature, structure orcharacteristic described in connection with the embodiment is includedin at least one embodiment described herein. References to oneembodiment within the specification do not necessarily all refer to thesame embodiment. The features illustrated or described in connectionwith one exemplary embodiment may be combined with the features of otherembodiments.

Also, the phraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting. The use herein of“including,” “comprising,” “having,” “containing,” “involving,” andvariations thereof is meant to encompass the items listed thereafter andequivalents thereof as well as additional items. References to “or” maybe construed as inclusive so that any terms described using “or” mayindicate any of a single, more than one, and all the described terms.Any references to front and back, left and right, top and bottom, upperand lower, and vertical and horizontal are intended for convenience ofdescription, not to limit the present systems and methods or theircomponents to any one positional or spatial orientation. Accordingly,the foregoing description and drawings are by way of example only, andthe scope of the invention should be determined from proper constructionof the appended claims, and their equivalents.

What is claimed is:
 1. A system for locating a mobile container within afacility comprising: an optical sensor system having at least oneoptical sensor fixed to a frame of the container, each optical sensorbeing pointed away from the container in a direction facing a region ofthe facility where one or more distinctive physical features areexpected to be found, each distinctive physical feature of the facilitybeing associated with a location in the facility, the at least oneoptical sensor being adapted to capture an image of that region of thefacility wherein one of the at least one optical sensor faces downwardstowards a floor of the facility; and a computing system in communicationwith the at least one optical sensor fixed to the frame of thecontainer, the computing system including a processor configured toreceive the image from the at least one optical sensor, to determinethat a physical feature found in the image matches one of thedistinctive physical features of the facility, and to identify thecontainer as being at the location in the facility associated with thematching distinctive physical feature.
 2. The system of claim 1, whereinthe optical sensor system includes an infrared projector for projectinga distinct pattern used by the computing system to calculate depth. 3.The system of claim 2, wherein the infrared projector is a cameraseparate from the at least one optical sensor.
 4. The system of claim 1,wherein the computing system is disposed remotely from the container andis configured to communicate wirelessly with the at least one opticalsensor to the receive the image.
 5. The system of claim 1, whereinanother of the at least one optical sensor faces upwards towards aceiling of the facility.
 6. The system of claim 1, further comprising adatabase storing images of the one or more distinctive physical featuresof the facility and associating each stored image with a location in thefacility.
 7. The system of claim 6, wherein the processor of thecomputing system is configured to match the physical feature in thecaptured image with a distinctive physical feature in a given imagestored in the database and to identify a location of the container asthe location associated with the given image in response to the match.8. The system of claim 1, further comprising a radio-frequency receiverdisposed on the container, the RF receiver receiving a radio signal at agiven radio frequency, and wherein the processor of the computing systemis configured to determine a location of the container based on arelative strength of the given frequency of the received radio signal.9. A method for locating a mobile container within a facilitycomprising: associating a distinctive physical feature of the facilitywith a location in the facility; acquiring, by an optical sensor fixedto a frame of the mobile container, an image of a region of thefacility, wherein the region of the facility in the acquired image is afloor of the facility; detecting a physical feature in the acquiredimage; matching the physical feature detected in the acquired image withthe distinctive physical feature of the facility; and identifying thecontainer as being at the location in the facility associated with thedistinctive physical feature in response to matching the physicalfeature detected in the acquired image with the distinctive physicalfeature of the facility.
 10. The method of claim 9, further comprisingacquiring, by another optical sensor fixed to the frame of thecontainer, an image of a ceiling of the facility.
 11. The method ofclaim 9, further comprising acquiring an image by another optical sensorfixed to the frame of the container facing horizontally parallel to thefloor of the facility.
 12. The method of claim 9, further comprising:storing images of distinctive physical features in the region of thefacility in a database; and associating each stored image with alocation in the facility.
 13. The method of claim 12, furthercomprising: matching the physical feature detected in the acquired imagewith a distinctive physical feature in a given image stored in thedatabase; and identifying a location of the container as the locationassociated with the given image in response to the match.
 14. The methodof claim 9, further comprising: receiving, by a receiver disposed on theframe of the mobile container, a radio signal having a given radiofrequency; and determining a location of the mobile container based on arelative strength of the given frequency of the received radio signal.